'sub' starting a word fragment
A neuronOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in layerOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. 26 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featuredA neuron picked for the full treatment: steering outputs and a written explanation. About 3,000 of the 86,000 neurons are featured., so it has steering outputs.
What this neuron does
This neuron fires most strongly on the piece 'sub' when it starts a longer word split across tokens, as in subcutaneous, subordinated or subunit. Turning it up made the model's text drift into unrelated topics, so it doesn't seem to steer the subject in any clear way.
Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).
Fires most on
The text windows where this neuron's activationThe number a neuron produces for a token. Large positive means it fired hard; negative means it pushed the other way. was highest. Amber marks positive activation; the outlined tokenA piece of text the model reads at once: often a word, sometimes part of a word or a punctuation mark. is the peak. Hover a token for its strength.
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called lean gene is not only linked to the risk of diabetes type 2 but also that of heart disease.⏎This gene IRS1 does lower fat, but only subcutaneous fat – fat under the skin, and not visceral fat, the fat
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organic chemistry laboratory for cooling reactions to sub-zero temperatures. Instead of using ice water to cool to 0 C, you
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in which the expectations are found are more⏎difficult. They will require a sophistication in manipulating⏎integrals, changing variables in integrals and using the Erf or⏎CumNorm functions. This would be a good task to use in this way
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only obstacle between the West and the fabulous contracts offered by Russia. All other matters should be subordinated to the trade—it’s a highly compelling argument.⏎The third thread paradoxically
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the plane after Kitaigorodsky . The upper arrangement has p2 plane group with twofold rotation, and the lower arrangement has pmm plane group with symmetry planes. In a complementary arrangement, the protrusion of one molecule complements
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of the muon (μ−⏎) and muon neutrino (νμ⏎) The third generation consist of the tau (τ−⏎) and the tau neutrino (ντ⏎). Each type of neutrino is associated with
SteeringAdding a push along a neuron while the model writes, to see how its output changes. Turning it up or down.
Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.
Here is something I have been thinking about lately: The polononore polononore polononore polononore polononore polononore polononore polononore polononore polononore polononore polonon
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
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learn how to obtain the Java Development Kit (JDK)⏎and write your first Java program.⏎Next, it's on to the Java fundamentals, including data types,⏎operators, control statements, classes, objects, and methods.⏎You'll then progress
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-like?<|endoftext|>& Tornado Alley⏎Jan Mikusinski developed an operational calculus which is relevant for solving differential equations. His operational calculus is based upon an algebra of the convolution of functions with respect to the Fourier transform. From the convolution product he
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, which begins with the study of functions and their derivatives and integrals⏎- The fundamentals of advanced algebra, which is based on axiomatic systems involving operations of addition and multiplication in general settings⏎- Additional subjects such as geometry, probability,
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and develop an understanding of the general principles and characteristics of programming and programming languages. This includes:⏎- algorithms and problem solving with an emphasis on fundamental data structures⏎- object-oriented programming⏎- event-driven programming.⏎At least some portion of a study
Connections
Show on mapWhich neuronsOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in earlier layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.
Fed by earlier layers
- L5:78 excites
- L10:276 excites
- L20:293 suppresses
- L5:2 suppresses
- L10:291 suppresses
- L3:105 excites
- L25:26 weakly suppresses
- L20:244 weakly excites
- L18:408 weakly excites
- L3:63 weakly excites
- L22:371 weakly excites
- L25:69 weakly excites
- L17:133 weakly excites
- L17:954 weakly suppresses
- L25:652 weakly suppresses
- L4:352 weakly suppresses
- L20:275 weakly excites
- L7:334 weakly excites
- L23:159 weakly excites
- L20:97 weakly excites
- L0:839 weakly suppresses
- L21:128 weakly excites
- L11:75 weakly suppresses
- L3:2248 weakly excites
Feeds later layers
- L27:111 weakly excites
- L27:2101 weakly excites
- L27:1048 weakly suppresses
- L27:2939 weakly excites
- L27:1213 weakly suppresses
- L27:971 weakly excites
- L27:70 weakly excites
- L27:1107 weakly excites
- L27:2532 weakly suppresses
- L27:2893 weakly excites
- L27:125 weakly excites
- L27:230 weakly suppresses
- L27:1097 weakly excites
- L27:2727 weakly suppresses
- L27:1725 weakly suppresses
- L27:1585 weakly excites
- L27:2085 weakly excites
- L27:1191 weakly excites
- L27:1554 weakly excites
- L27:3057 weakly excites
- L27:2927 weakly excites
- L27:2451 weakly excites
- L27:2968 weakly excites
- L27:757 weakly excites
Activation histogramA chart of how often a neuron takes each activation value.
How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.
Logit lensReading which output tokens a neuron pushes toward or away from, straight off its output weights, before the later layers have their say.
The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. instead.
Promotes
- rams
- unction
- (stats
- argument
- 积分
- ParameterValue
- _arguments
- (vars
- RefCount
- -character
Suppresses
- чная
- riz
- pol
- 缮
- .pol
- advis
- nâ
- ural
- 不开
- Indo